2007
DOI: 10.1121/1.2642137
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Quantifying the uncertainty of geoacoustic parameter estimates for the New Jersey shelf by inverting air gun data

Abstract: This paper describes geoacoustic inversion of low frequency air gun data acquired during an experiment on the New Jersey shelf. Hybrid optimization and Bayesian inversion techniques based on matched field processing were applied to multiple shots from three air gun data sets recorded by a vertical line array in a long-range shallow water geometry. For the Bayesian inversions, full data error covariance matrix was estimated from a set of consecutive shots that had high temporal coherence and small spatial varia… Show more

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Cited by 42 publications
(19 citation statements)
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“…20 The in situ water sound speed measurements on the NRL300 source mooring and a bottom model provided by a previous study 21 are used in the program. The calculation results, shown in Fig.…”
Section: Experimental Datamentioning
confidence: 99%
“…20 The in situ water sound speed measurements on the NRL300 source mooring and a bottom model provided by a previous study 21 are used in the program. The calculation results, shown in Fig.…”
Section: Experimental Datamentioning
confidence: 99%
“…Geoacoustic inversion using noise field spatial coherence from low frequency air gun sources had been carried out by Jiang and Chapman 8 and the uncertainty of geoacoustic parameter estimates had been quantified. A time domain matched beam processing was also attempted by Jiang et al, 9 using broadband data from a long range propagation experiment, and the estimates agree well with ground truth information. Yang et al, 10 used a source and a ship towed line array system for estimating bottom properties and sub-bottom profiling.…”
Section: Introductionmentioning
confidence: 77%
“…Figure 3 (left panel) shows the compressional wave speeds in the top 40 m of the sediments estimated by the inversion scheme. The dashed line is the geoacoustic model proposed by Jiang et al (2007). They suggested this model for the SW06 experimental area based on chirp sonar inversions, grab samples, in situ probes, and shallow core measurements.…”
Section: Iterative Scheme To Estimate the Compressional Wave Speedmentioning
confidence: 99%
“…A geoacoustic model based on historic data from the experimental location (Jiang et al, 2007) was used in the beginning to initialize the parameter d͑u , ͒. Group velocities corresponding to each normal mode were used to compute d͑u , ͒ which were then assigned to time-frequency locations in the neighborhood of the normal mode.…”
Section: Iterative Scheme To Estimate the Compressional Wave Speedmentioning
confidence: 99%